Method and device for monitoring the environment of a vehicle and method for performing an emergency braking maneuver

Abstract

Method for monitoring the environment of a vehicle (300) comprising the following steps: Reading (551) a distance image (200) with respect to the surroundings of the vehicle (300), wherein the distance image (200) comprises a plurality of distance values ​​representing the result of a plurality of distance measurements carried out using a sensor (332) for stereo image acquisition with respect to the surroundings of the vehicle (300) detected by the sensor (332); Selecting (553) a section (100) from the distance image (200); Detect (555) an obstacle (110) located in the environment, using the distance values ​​contained in the section (100); Determine (557) a number and quality of relevant distance values ​​that represent distance values ​​contained in the section (100) that can be assigned to the obstacle (110); Determining (559) a value of an existence measure for the existence of the obstacle (110) based on the number and quality of the relevant distance values, wherein the value of the existence measure is determined depending on a ratio between the number and quality of the relevant distance values ​​and a total number of distance values ​​contained in the section or a ratio between the number and quality of the relevant distance values ​​and a number of the other distance values ​​present in the section; Providing a warning signal when the value of the existence measure represents an actual presence of the obstacle (110); and Checking whether the emergency braking of the vehicle (300) is necessary to avoid a collision between the vehicle (300) and the obstacle (110) using the warning signal.

Description

State of the art

[0001] The present invention relates to a method and a device for monitoring the surroundings of a vehicle and to a method for performing an emergency braking of a vehicle.

[0002] Emergency braking systems based on environmental sensors are increasingly being introduced onto the market. Since these involve safety-critical interventions in vehicle movement, achieving and demonstrating very low error rates is essential. This can be achieved, for example, through a sufficient number of hours of representative driving statistics and recording the required sensor data. However, this requires considerable effort for data acquisition and the necessary infrastructure for data recording and re-simulation. The representative driving effort is typically at least in the range of several tens of thousands of hours; however, depending on the intervention intensity of the emergency braking system, the required number of hours can be significantly higher.

[0003] DE 10 2009 009 047 A1 discloses a method for object detection in which two images of an environment are taken and a disparity image is determined by means of stereo image processing, wherein a depth map of the environment is determined from the determined disparities.

[0004] DE 196 36 028 C1 discloses a method for detecting objects using stereo image analysis. Using an analysis window, the number of pixels to be considered can be reduced.

[0005] DE 199 26 559 A1 discloses a method for detecting objects in the vicinity of a road vehicle at great distances. Distance-based image segmentation using stereo image processing and object recognition in the segmented image areas are performed.

[0006] DE 10 2009 052 868 A1 discloses a method for operating a driver assistance system of a vehicle, wherein images of an environment of the vehicle are captured by means of at least two cameras and are stereoscopically processed by means of an image processing unit to form a disparity map and / or depth map. Disclosure of the invention

[0007] Against this background, the present invention presents a method and a device for monitoring the surroundings of a vehicle, as well as a method for performing emergency braking of a vehicle, according to the main claims. Advantageous embodiments emerge from the respective subclaims and the following description.

[0008] A stereo image capture device, such as a stereo camera, can be used to monitor the surroundings of a vehicle. The stereo image capture device can be used to measure distances. A distance image generated using the stereo image capture device using known methods for calculating a stereo video disparity map can be used to detect an obstacle located in the monitored environment. Only a section of the distance image can be evaluated to detect the obstacle. In this way, the complexity of evaluating a stereo image capture device can be kept to a minimum.

[0009] A method for monitoring the environment of a vehicle comprises the following steps: Reading in a distance image with respect to the surroundings of the vehicle, wherein the distance image comprises a plurality of distance values ​​representing the result of a plurality of distance measurements carried out using a sensor for stereo image capture with respect to the surroundings of the vehicle captured by the sensor; Selecting a section from the distance image; Detecting an obstacle in the environment using the distance values ​​contained in the section; Determining a number and quality of relevant distance values ​​that represent distance values ​​contained in the section that can be assigned to the obstacle; and Determining a value of an existence measure for an existence of the obstacle based on the number and quality of relevant distance values.

[0010] The distance image can represent an image based on known methods for calculating stereo video disparity maps. In other words, the distance image can be or have been created using known methods for calculating stereo video disparity maps. The relevance of a distance value, i.e., whether a distance value is considered relevant or not, can be defined by considering the distance value as relevant if it lies within a distance interval of defined length. Thus, the distance values ​​can be checked to see whether they lie within the distance interval of defined length. The quality of a distance value can be a measure of the probability that the distance value actually lies within the distance interval.For example, the quality of a distance value can be higher the more reliably it can be assumed that the distance value lies within the distance interval. The quality can also be based on secondary parameters that can be determined, for example, during the disparity calculation. The quality can also represent the accuracy of a distance value or the usability of a distance value for determining the existence of an obstacle. The higher the quality of a relevant distance value, the more it indicates the existence of the obstacle.

[0011] The vehicle can be a motor vehicle, for example a passenger car, a truck, or a motorcycle. The surroundings can be an area in front of the vehicle in the direction of travel, for example a section of a roadway. The sensor for stereo image capture can be arranged on the vehicle. Data captured by the sensor can be evaluated using a suitable evaluation device. Each pixel of the distance image can be assigned a distance value. In this way, the distance image can be used to determine a distance between the sensor for stereo image capture and any surroundings captured by the sensor for stereo image capture. The distance image can be understood as a list of distance values ​​assigned to an image coordinate. The distance image can be in digital form.The distance image or data representing the distance image can be read in via an interface to the sensor for stereo image acquisition or to an evaluation device downstream of the sensor for stereo image acquisition. The section from the distance image can be a region of the distance image relevant for detecting the obstacle. The section can also be referred to as an evaluation window. For example, the section can represent an image region of the distance image with a vertical and a horizontal image angle of, for example, less than 25°, less than 15°, less than 10° or less than 5°. Using known evaluation methods, an obstacle located in the surrounding area can be detected using the distance values ​​contained in the section. In particular, an obstacle can be detected that is imaged by the section of the image area.The obstacle can be a stationary or moving object, such as an external vehicle. Object recognition methods can be used to assign a distance value to the obstacle. The more distance values ​​with the appropriate quality that can be assigned to the obstacle, the higher the probability that the obstacle actually exists. For example, the value of the existence measure can be higher, the higher the probability that the obstacle actually exists.

[0012] The method may include a step of providing a warning signal if the value of the existence measure represents the actual presence of the obstacle. The warning signal may be used, for example, by a safety system or a driver assistance system of the vehicle.

[0013] The method may include a step of checking whether the vehicle requires emergency braking to avoid a collision between the vehicle and the obstacle using the warning signal. For example, the warning signal may be used to verify the need for emergency braking. The warning signal may also be used to validate an emergency braking signal for triggering emergency braking.

[0014] In the selection step, a section located centrally in the distance image can be selected as the section. Such a section can be predefined. This simplifies the analysis of the distance image.

[0015] During the selection step, an edge of the section facing the ground can be selected such that, if an obstacle is present at a predetermined distance from the sensor, the section detects the obstacle from a predetermined height above the ground. This allows a so-called collision relevance height to be taken into account. In this way, the section can detect an obstacle that poses an immediate danger to the vehicle due to its proximity to the vehicle and its size.

[0016] The value of the existence measure can be determined in the determination step depending on a ratio between the number and quality of the relevant distance values ​​and the total number of distance values ​​contained in the excerpt, or a ratio between the number and quality of the relevant distance values ​​and the number of remaining distance values ​​present in the excerpt. In this way, the value can be determined very easily and quickly. Furthermore, the number and distribution of valid distance values, which is typically in the range of several thousand, can provide further information about the statistical quality of the existence measure.

[0017] For example, the value of the existence measure can be determined in the determination step such that the value of the existence measure indicates the actual existence of the obstacle if the number of relevant distance values ​​exceeds a threshold. Likewise, the value of the existence measure can be determined in the determination step such that the value of the existence measure indicates the actual existence of the obstacle if the ratio between the number of relevant distance values ​​with sufficient quality and the number of the remaining distance values ​​present in the section exceeds a threshold. Thus, a simple threshold comparison can be used to determine whether an obstacle is present or not. In addition, a standard deviation can be calculated using the distribution of the valid distance values, which can also be used as a threshold for the validity of the existence measure.

[0018] The method may include a step of determining a distance to the obstacle using the relevant distance values. Thus, the distance image can be used additionally to determine the distance between the vehicle and the obstacle.

[0019] In the determination step, a relative speed between the obstacle and the vehicle can be determined using the distance. For this purpose, several distances to the obstacle can be determined, for example, based on distance images acquired one after the other. The relative speed can be determined based on the multiple distances and the times the distance images were acquired. Information about the relative speed can, for example, be used to decide whether emergency braking is necessary.

[0020] Such an approach can be used, for example, to enable an emergency braking system based on validated sensor or system models on a smaller data basis than that generated by the stereo image capture system as a whole. The restrictions and simplifications introduced, such as the definition of an "evaluation window" located at the collision-relevant height above the road surface, as well as a simple and statistically meaningful procedure for determining a measure of existence, allow system malfunctions, for example, caused by environmental influences (rain, fog, snow, etc.), to be better modeled with regard to their critical impact (e.g., "false positives") than would be possible for the entire stereo image capture range.In this sense, the proposed method for evaluating a stereo image capture device represents a kind of emulation of a known simple and easier to validate sensor principle, namely that of a single-beam lidar geometry (see below).

[0021] This means that the driving hours required for system approval can be essentially limited to the conditions and situations classified as relevant based on the model knowledge, or can be partially or completely avoided using the available a priori knowledge. The required model knowledge can be generated theoretically or through targeted test series to determine the system behavior with regard to the relevant faults. This makes it possible to build on well-understood and valid statistical models that allow the system behavior to be determined with regard to the set safety goal. In this sense, validation and approval are steered in the direction of the approach used for ESP or airbag systems, for example. In the case of ESP, for example, defined driving maneuver catalogs that contain corresponding extreme scenarios are tested. This makes large-scale field testing for system approval unnecessary if necessary.only in a limited form or, at best, no longer necessary at all.

[0022] The described approach is a novelty, as such models have not yet existed for driver assistance systems based on environment sensors requiring complex evaluation technology, such as video or radar sensors, due to the high complexity of the environment model to be created and the multitude of resulting deficiencies. The correspondingly complex models of driver assistance signal processing chains usually contain deficiencies or specification gaps that prevent any conclusions regarding the achievement of the set safety goals. If, for example, a radar sensor is used, this complexity arises from the fact that the entire backscatter behavior of all surrounding radar-reflecting objects cannot be fully modeled in all statistically relevant driving situations.

[0023] Exceptions to this may be environment sensor-based driver assistance systems with very simple measurement or environment interpretation principles related to a limited classification task. For example, a single-beam lidar can be used as an environment sensor, where the classification task "collision-relevant object is in the driving path" is realized using a simple, robust, and easily modelable measurement principle. Key features can be a "sharp" beam geometry, which creates an "evaluation window" defined by the collision-relevant height above the road surface, as well as a "time-of-flight" distance measurement. Deficiencies in the measurement principle that could lead to potential "false positives," such as environmental influences or leafy branches extending into the sensor beam, are easily modeled and evaluated and are not the result of complex signal processing.

[0024] A method for performing an emergency braking of a vehicle to avoid or mitigate the severity of a collision between the vehicle and an obstacle located in the vicinity of the vehicle comprises the following steps: Performing the steps of a said method for monitoring the surroundings of the vehicle to determine a value of an existence measure for the existence of the obstacle; and Carrying out emergency braking depending on the value of the existence measure.

[0025] Thus, an evaluation procedure for the efficient validation of a stereo video emergency braking system can be realized.

[0026] A device for monitoring the surroundings of a vehicle has the following features: a device for reading a distance image with respect to the surroundings of the vehicle, wherein the distance image comprises a plurality of distance values, which represent the result of a plurality of distance measurements carried out using a sensor for stereo image capture with respect to the surroundings of the vehicle detected by the sensor; means for selecting a section of the distance image; a device for detecting an obstacle in the environment using the distance values ​​contained in the section; a device for determining a number and quality of relevant distance values ​​that represent distance values ​​contained in the section that can be assigned to the obstacle; and means for determining a value of an existence measure for an existence of the obstacle based on the number and quality of relevant distance values.

[0027] The determining device can further be configured to determine the value of the existence measure based on an evaluation of the distance distribution. The distance distribution can represent a distribution of distance values.

[0028] The devices of such a device can be used to implement the steps of said method for monitoring an environment of a vehicle.

[0029] A device for performing emergency braking of a vehicle to avoid a collision between the vehicle and an obstacle located in a surrounding of the vehicle may further comprise a device for performing the emergency braking depending on the value of the existence measure.

[0030] In this case, a device can be understood as an electrical device that processes sensor signals and outputs control and / or data signals depending on them. The device can have an interface, which can be implemented in hardware and / or software. In a hardware implementation, the interfaces can, for example, be part of a so-called system ASIC, which contains a wide variety of functions of the device. However, it is also possible for the interfaces to be separate integrated circuits or to consist at least partially of discrete components. In a software implementation, the interfaces can be software modules that are present, for example, on a microcontroller alongside other software modules.

[0031] Also advantageous is a computer program product with program code that can be stored on a machine-readable medium such as a semiconductor memory, a hard disk memory, or an optical memory and is used to carry out the method according to one of the embodiments described above, when the program code is executed on a computer or device. Thus, the steps of the method defined in the program code can be implemented by devices of the computer or device.

[0032] The invention is explained in more detail below with reference to the accompanying drawings. They show: Fig. 1 a schematic representation of a section of an image of the surroundings of a vehicle; Fig. 2 a representation of a distance image; Fig. 3 is a schematic representation of a vehicle with a device for monitoring the surroundings of a vehicle; Fig. 4 is a schematic representation of a device for monitoring the surroundings of a vehicle; Fig. 5 is a flowchart of a method for monitoring the surroundings of a vehicle; and Fig. 6 a schematic representation of an obstacle in the vicinity of a vehicle.

[0033] In the following description of preferred embodiments of the present invention, the same or similar reference numerals are used for the elements shown in the various figures and having a similar effect, whereby a repeated description of these elements is omitted.

[0034] Fig. 1 shows a schematic representation of a section 100 from an image 102 of the surroundings of a vehicle according to an exemplary embodiment of the present invention. The image 102 can be an image captured by a sensor for stereo image capture. The image 102 depicts a section of a roadway in front of the vehicle and an external vehicle 110 located on the roadway. The external vehicle 110 can be a vehicle traveling ahead of the vehicle. The external vehicle 110 can be recognized by evaluating a distance image captured by the sensor for stereo image capture. In a distance image, each of the Fig. A distance value can be assigned to the pixels of image 102 shown in Figure 1. A distance value can represent a distance between the sensor for stereo image capture and an object section represented by the corresponding pixel. Such distance values ​​can be determined from a stereo image using known methods by calculating an associated disparity map.

[0035] According to this exemplary embodiment, the section 100 is arranged centrally in the image 102. The section 100 can, for example, comprise less than 20% of the entire image 102. According to this exemplary embodiment, the section 100 is rectangular, for example, square.

[0036] A position of the section 100 within the image 102 is selected such that the other vehicle 110 is imaged through the section 100 when the other vehicle 110 is located at a collision-relevant distance in front of the vehicle having the sensor for stereo image capture. At a collision-relevant distance, depending on the relative speed between the other vehicle 110 and the vehicle, emergency braking of the vehicle may be necessary to avoid a collision with the other vehicle 110.

[0037] To detect the other vehicle 110 or generally an obstacle in the vehicle's surroundings, the section 100 of the image, which is also referred to below as the evaluation window, can be evaluated. In this case, an evaluation of a stereo video disparity map assigned to the image 102 can be performed in the defined evaluation window.

[0038] Fig. Figure 2 shows a representation of a distance image 200 according to an embodiment of the present invention. The distance image 200 is also referred to below as a disparity map. The distance image 200 can be based on data acquired by a sensor for stereo image acquisition. The distance image 200 can be based on Fig. 1, but in a different situation in the vehicle's surroundings. Here, a distance image 200 is shown in the form of a "dense" disparity map. The different brightness ranges visible in the distance image 200 correspond to different distance values. For example, a pixel in a region 221 can be assigned a larger distance value than a pixel in a region 222.

[0039] Fig. 3 shows a schematic representation of a vehicle 300 with a device 330 for monitoring the surroundings of the vehicle 300 according to an exemplary embodiment of the present invention. The vehicle 300 has a sensor 332 for stereo image acquisition. The sensor 332 can be a stereo video sensor. The sensor 332 is designed to acquire an image of the surroundings of the vehicle 330 at an image angle 334. Based on the image data acquired at the image angle 334, a distance image comprising a plurality of distance values ​​can be determined. Such a distance image can be read in by the device 330 for monitoring the surroundings of the vehicle 300 via a suitable interface. Based on a section of the distance image, an obstacle located in the surroundings of the vehicle 300 can be detected if it is located in the area of ​​the distance image covered by the section.Device 330 is configured to detect such an obstacle based on the section of the distance image and to determine a value for a measure of existence, which may represent a probability of the obstacle's actual existence. The section may, for example, be arranged centrally in the distance image. For example, the section may comprise a region of the distance image that is captured by the sensor 332 for stereo image capture at an image angle 336 that covers a partial area of ​​the image angle 334.

[0040] Device 330 can be configured to output the value for the existence measure via an interface. According to a further embodiment, device 330 is configured to further process the value for the existence measure and, for example, to determine a warning signal based on the value for the existence measure and output it via a suitable interface to an optional device 340 for performing emergency braking of vehicle 300. Thus, device 330 can be part of a stereo-image emergency braking system.

[0041] Fig. Figure 4 shows a schematic representation of a device 330 for monitoring the surroundings of a vehicle according to an embodiment of the present invention. This can be the device 330 described with reference to Fig. 3 described device 330.

[0042] The device 330 has a device 451 that is designed to read in a distance image with respect to the surroundings of the vehicle. The distance image can be generated based on data from a sensor for stereo image acquisition and can have a plurality of distance values. Each image area, for example each pixel of the distance image, can be assigned a distance value. Furthermore, the device 330 has a device 453 that is designed to select a section from the distance image. The section can be the section determined based on Fig. 3 described section. A device 455 is designed to detect an obstacle located in the environment using the distance values ​​contained in the section. A device 457 is designed to determine a number of relevant distance values ​​that represent distance values ​​contained in the section that can be assigned to the obstacle. This can be done by simply counting the corresponding distance values ​​with sufficient quality. A device 459 is designed to determine a value of an existence measure for the existence of the obstacle, specifically using the number and quality of relevant distance values. For example, the device 459 can be designed to determine the value of the existence measure by performing a threshold comparison.For this purpose, the number and quality of relevant distance values ​​or a ratio of the number and quality of relevant distance values ​​and a total number of distance values ​​of the section or the remaining distance values ​​of the section can be compared with one or more thresholds.

[0043] Fig. Figure 5 shows a flowchart of a method for monitoring the surroundings of a vehicle according to an embodiment of the present invention. The method can be implemented, for example, using the devices of the Fig. 4 described device.

[0044] The method comprises a step 551 of reading in a distance image relating to the surroundings of the vehicle. The distance image can comprise a plurality of distance values ​​representing the result of a plurality of distance measurements carried out using a sensor for stereo image capture with respect to the surroundings of the vehicle detected by the sensor. In a step 553, a section is selected from the distance image, and in a step 555, an obstacle located in the surroundings is detected using the distance values ​​contained in the section, provided such an obstacle is present. In a step 557, a number of relevant distance values ​​are determined, representing distance values ​​contained in the section that can be assigned to the obstacle.In a step 559, a value of an existence measure for an existence of the obstacle is determined based on the number and quality of relevant distance values.

[0045] Fig. Figure 6 shows a schematic representation of an obstacle 110 in the surroundings of a vehicle 300 according to an exemplary embodiment of the present invention. The obstacle 110 may, for example, be an object lying on a roadway that could pose a hazard to the vehicle 300 if the vehicle 300 were to collide with the obstacle 110.

[0046] The vehicle 300 is equipped with a device for monitoring the surroundings of a vehicle, as described, for example, by Fig. 4. The monitoring device is designed to evaluate a section of a distance image. The section of the distance image is shown in Fig. 6 by an aperture cone 636, which represents a subset of the entire aperture cone of a stereo image capture device of the vehicle 300. The section is selected such that it is located at a predetermined distance from the sensor at a predetermined height h above the ground. Based on the section, a collision relevance classification can be performed using a sensor mounted here at the top of the vehicle 300.

[0047] With reference to the preceding figures, exemplary embodiments of the present invention are described in detail below.

[0048] The ability to create sensor and system models that allow for the identification of deficiencies and specification gaps with regard to a set safety objective depends essentially on the complexity of the measurement or interpretation principle of the environmental sensor used, for example a sensor 332. In the case of an environmental sensor 332 that is complex in terms of evaluation technology, such as a stereo video sensor, for which a large number of original image pixels must be evaluated per time step (typically in the order of 1 million), an evaluation procedure is defined with which a sensor model that is comparatively simple in terms of validation can be created. The aim here is to form the environmental object hypotheses required for the system with the lowest possible complexity and with few, comprehensible assumptions. Any limitations and deficiencies that may arise, for example,The impact of the tests that result in “false positives” is clearly identifiable.

[0049] This is made possible by a robust evaluation principle for a stereo video sensor 332, which allows for simple modeling in the sense described above. The basic measurement principle of a stereo video sensor 332 consists in the calculation of a disparity map 200, which essentially represents a high-resolution distance image of the image area it contains, as shown in Fig. 2 is shown.

[0050] In the following, it is assumed, without loss of generality, that the ego vehicle 300 is always on a drivable surface. In the vast majority of cases, this road surface, usually an asphalt road, is observable by a sensor 330 in the form of a stereo camera and can be reconstructed from the disparity map 200 using regression methods. Regarding the evaluation of the disparity map 200 with regard to a classification task "collision-relevant object 110 is located in the driving path", i.e. the classification of an object 110 as a barrier, an evaluation window is defined on a centrally arranged section 100 in the image 110, as shown in Fig. 1. This defines a similarly "sharp" optical demarcation as in the measurement by a lidar beam. Thus, a kind of emulation of a lidar beam geometry can be carried out by evaluating a video image in a defined area 100. For example, the Fig. The aperture cone 636 shown in Figure 6 can be understood as an emulation of a lidar beam.

[0051] For a collision relevance analysis, a device 330 in the form of a barrier detector provides a presence measure in addition to the distance to the nearest barrier 110. This essentially indicates how many of the total disparity measurements present in the evaluation window 100 lie on the barrier 110.

[0052] If the presence of a barrier 110 exceeds a predefined threshold, the obstacle 110 is taken into account in the event of an impending collision, triggering an emergency braking maneuver. The distance to the barrier 110 is measured by averaging, typically several thousand disparity values, which enables a high-quality distance determination along the longitudinal vehicle axis. From this, the longitudinal relative velocity can be determined as a derived value, e.g., using a Kalman filter, and used to determine the collision probability.

[0053] The described embodiments enable the implementation of a simple, robust evaluation principle for object hypothesis generation for an emergency braking system based on stereo-video sensor technology. This, in other words, allows the measurement to be traced back integrally to a single distance window 100, analogous to a "time of flight" evaluation, i.e., a travel time evaluation of a single lidar beam.

[0054] A reduction in the safeguarding effort for a system release, for example for carrying out an emergency braking, can be achieved by the fact that the deficiencies regarding classification errors with regard to the obstacle 110, e.g. the occurrence of so-called false positives, can be well described and modeled.

[0055] The exemplary embodiments described and shown in the figures are selected only as examples. Different exemplary embodiments can be combined with one another in their entirety or with regard to individual features. An exemplary embodiment can also be supplemented by features of another exemplary embodiment. Furthermore, method steps according to the invention can be repeated and performed in a different order than the one described.

Claims

[1] A method for monitoring an environment of a vehicle (300), comprising the following steps: Reading (551) a distance image (200) with respect to the surroundings of the vehicle (300), wherein the distance image (200) comprises a plurality of distance values ​​representing the result of a plurality of distance measurements carried out using a sensor (332) for stereo image acquisition with respect to the surroundings of the vehicle (300) acquired by the sensor (332); Selecting (553) a section (100) from the distance image (200); Detecting (555) an obstacle (110) located in the environment using the distance values ​​contained in the section (100); Determining (557) a number and quality of relevant distance values ​​that represent distance values ​​contained in the section (100) that can be assigned to the obstacle (110); Determining (559) a value of an existence measure for an existence of the obstacle (110) based on the number and quality of the relevant distance values, wherein the value of the existence measure is determined depending on a ratio between the number and quality of the relevant distance values ​​and a total number of the distance values ​​contained in the section or a ratio between the number and quality of the relevant distance values ​​and a number of the remaining distance values ​​present in the section; Providing a warning signal if the value of the existence measure represents an actual presence of the obstacle (110); and Testing an emergency braking of the vehicle (300) required to avoid a collision between the vehicle (300) and the obstacle (110) using the warning signal. [2] Method according to claim 1, wherein in the step of selecting (553) a section arranged centrally in the distance image (200) is selected as the section (100). [3] Method according to one of the preceding claims, wherein in the step of selecting (553) an edge of the section facing the ground is selected such that the section (100), in the presence of an obstacle (110) located at a predetermined distance from the sensor (332), detects the obstacle (110) from a predetermined height above the ground. [4] Method according to one of the preceding claims, wherein the value of the existence measure is determined in the determining step (559) such that the value of the existence measure indicates the actual existence of the obstacle (110) when the number of relevant distance values ​​exceeds a threshold value. [5] Method according to one of the preceding claims, comprising a step of determining a distance to the obstacle (110) using the relevant distance values. [6] Method according to claim 5, wherein in the step of determining using the distance a relative speed between the obstacle (110) and the vehicle (300) is determined. [7] Method for performing an emergency braking of a vehicle (300) to avoid or reduce the severity of a collision between the vehicle (300) and an obstacle (110) located in an environment of the vehicle (300), the method comprising the following steps: Carrying out the steps (551, 553, 555, 557, 559) of a method for monitoring the surroundings of the vehicle (300) according to one of the preceding claims to determine a value of an existence measure for an existence of the obstacle (110); and Carrying out emergency braking depending on the value of the existence measure. [8] Device for monitoring the surroundings of a vehicle (300), having the following features: a device (451) for reading in a distance image with respect to the surroundings of the vehicle (300), wherein the distance image comprises a plurality of distance values ​​representing the result of a plurality of distance measurements carried out using a sensor (332) for stereo image detection with respect to the surroundings of the vehicle (300) detected by the sensor (332); means (453) for selecting a section (100) from the distance image (200); a device (455) for detecting an obstacle (110) located in the environment, using the distance values ​​contained in the section (110); means (457) for determining a number of relevant distance values ​​representing distance values ​​contained in the section (100) that can be assigned to the obstacle (110); and a device (459) for determining a value of an existence measure for an existence of the obstacle (110) based on the number and quality of relevant distance values, wherein the value of the existence measure is determined as a function of a ratio between the number and quality of the relevant distance values ​​and a total number of the distance values ​​contained in the section or a ratio between the number and quality of the relevant distance values ​​and a number of the remaining distance values ​​present in the section; means for providing a warning signal when the value of the existence measure represents an actual presence of the obstacle (110); and a device for checking an emergency braking of the vehicle (300) required to avoid a collision between the vehicle (300) and the obstacle (110) using the warning signal.

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